「metric」の検索結果

Use when the user asks to "run a launch retro / post-mortem", "compare launch results vs targets by channel", or "decide what to keep or kill for the next launch"; produces a structured D1/W1/M1 retrospective — a per-channel actual-vs-target table (UTM-attributed own analytics as the truth column, platform self-reported numbers as reference, every figure labeled Measured / User-provided / Estimated), a 5-Whys chain on the single largest miss, keep / kill / change decisions per channel, 3-5 actionable learnings for the next launch, and an outcome snapshot submitted to the launch registry. Not for return math (CPA / ROI) — use roi-calculator; not for the stakeholder-facing report writeup — use report-generator; not for a metric deep-dive — use performance-analyzer. 发布复盘/渠道归因/5-Whys/keep-kill

日本語の概要は準備中です。原文の説明を表示しています。

Use when the user asks to "monitor my launch", "track our Product Hunt / Hacker News ranking", or "watch the launch window"; runs the T-0 to T+30 window watch — pre-launch instrumentation verification (UTM/event checks, the upstream of RAMP P1), HN rank/points/comments polling with a comments-over-points flamewar early-warning (Estimated heuristic), PH votes/featured status, store charts and reviews, news echo, D0/W1/M1 KPI snapshots vs targets, spike-vs-sustain and owned-capture reads, and alert thresholds against the launch-tier KPI targets. Not for launch-day go/rollback calls — use launch-day-conductor; not for metric deep-dives — use performance-analyzer; not for SEO rank tracking — use rank-tracker. 发布监控/排名轮询/火焰战比/spike-sustain

日本語の概要は準備中です。原文の説明を表示しています。

Use when the user asks to "analyze backlinks", "analyze my off-site signals", or "track AI traffic / ChatGPT / Perplexity referrals"; profiles referring domains, anchor-text mix, toxic links, and disavow candidates (backlinks mode) or isolates AI-assistant referral sessions in GA4/GSC/logs and reports their trend, landing pages, and AI-vs-organic conversion (ai-referrals mode). Not for internal links — use site-structure-optimizer; not for keyword positions — use rank-tracker; not for multi-metric stakeholder reports — use performance-monitor. 外链分析/反向链接/AI流量/AI引荐/ChatGPT流量/AI转化

日本語の概要は準備中です。原文の説明を表示しています。

Use when the user asks to "track rankings" or "查排名"; measures keyword and SERP-position deltas over time from provided exports or connected tools, including AI-response checks. Not for multi-metric stakeholder reports or setting alerts — use performance-monitor (report or alert mode). 排名追踪/SERP监控

日本語の概要は準備中です。原文の説明を表示しています。

Use when the user asks to "generate an SEO report", "出月报", "set SEO alerts", or "排名掉了提醒我"; two modes — report builds multi-metric traffic/ranking/authority/content dashboards, and alert configures threshold notifications for future ranking, traffic, technical, backlink, competitor, and AI-visibility changes. Not for raw position-by-position deltas — use rank-tracker. SEO报告/绩效仪表盘/SEO预警/排名监控

日本語の概要は準備中です。原文の説明を表示しています。

Use when the user asks to "create a campaign report", "build an executive summary", or "deliver client results"; produces audience-tailored influencer marketing reports (executive, client, internal team) with data tables, narrative, key learnings, and recommendations. Not for raw metric computation — use performance-analyzer. 达人营销报告/结案汇报

日本語の概要は準備中です。原文の説明を表示しています。

Use when the user asks to "analyze influencer campaign performance", "compare influencers", or "find what content worked"; produces metric scorecards vs target and benchmark, platform/influencer/content rankings, engagement-quality and sentiment reads, conversion-attribution breakdowns, and ranked learnings. Not for dollar-level return math — use roi-calculator. 达人营销效果分析/投放复盘

日本語の概要は準備中です。原文の説明を表示しています。

Design an A/B experiment — hypothesis, variants, primary metric, and sample size. Use when a change can be measured quantitatively at scale. For observing behaviour qualitatively, use `test-scenario`.

日本語の概要は準備中です。原文の説明を表示しています。

Design a usability study — research questions, methodology, participant criteria, metrics, and facilitation guide. Use when planning the study as a whole. For writing the task scenarios inside it, use `test-scenario` (prototyping-testing).

日本語の概要は準備中です。原文の説明を表示しています。

Read funnels, retention curves, and event data as a designer — separating a design problem from a tracking artefact. Use when handed product data you did not design and asked why people drop off. For choosing what to measure, use `metrics-definition` (ux-strategy); for running a controlled test, use `a-b-test-design` (prototyping-testing).

日本語の概要は準備中です。原文の説明を表示しています。

Show session analytics, learning patterns, correction trends, heatmaps, and productivity metrics. Computes stats from project memory and session history. Use when asking for stats, statistics, progress, how am I doing, coding history, or dashboard.

日本語の概要は準備中です。原文の説明を表示しています。

Debugs AWS Lambda function timeout failures by systematically analyzing function configuration, CloudWatch logs and metrics, VPC/networking, cold starts, memory constraints, and downstream dependencies to identify root causes with actionable fixes. Use when a Lambda function is timing out or approaching its timeout limit.

日本語の概要は準備中です。原文の説明を表示しています。

Retrieves authoritative guidance on Amazon Timestream for InfluxDB across its supported engine variants. Applicable to any InfluxDB-on-AWS request including engine variant and licensing selection, provisioning and IAM, encryption at rest (AWS-owned and customer-managed KMS keys, key policies, and key lifecycle), schema design (tags vs fields, cardinality, HTTP/sensor/metric data modeling), migration from LiveAnalytics, Processing Engine plugins, connectivity (database endpoints and private or public access), and write/query errors.

日本語の概要は準備中です。原文の説明を表示しています。

Installs, configures, and troubleshoots Network Flow Monitor agents on EC2 instances to monitor network path health. Covers agent installation, IAM permissions, monitoring network paths, and troubleshooting agents reporting no metrics, HTTP 403 errors, or connectivity failures.

日本語の概要は準備中です。原文の説明を表示しています。

Operates Amazon Kinesis Data Streams (KDS). Covers streaming tables and Amazon S3 delivery - serverless, fully managed delivery from a KDS stream to Apache Iceberg tables on S3 Tables or to general-purpose S3 buckets. Includes channel setup, IAM, schemas, output key templates, CloudWatch metrics and alarms, DLQ handling, quotas, and troubleshooting. For all other KDS topics and questions, search AWS documentation and blogs instead. Triggers: Kinesis Data Streams, KDS, streaming tables, stream to S3, stream to Iceberg, stream to S3 Tables, KDS delivery, KDS channel, CreateChannel, data channel, data freshness, dead-letter queue, KDS lakehouse, serverless Kinesis delivery, Firehose alternative for KDS, zero-ops Kinesis to S3. DO NOT USE for Kinesis Data Firehose, Kinesis Video Streams, or Managed Service for Apache Flink — use dedicated skills or search documentation instead.

日本語の概要は準備中です。原文の説明を表示しています。

Selects, deploys, and customizes AI models on Amazon SageMaker. Training or Processing jobs, fine-tuning (SFT/DPO/RLVR/RLAIF), model selection, dataset preparation, evaluation, SageMaker or Bedrock deployment, inference optimization and endpoint diagnostics. Covers the full lifecycle from planning through production. Use when fine-tuning models on SageMaker, choosing which base model to customize, fine-tune, or deploy from SageMaker JumpStart or Hub, SageMakerPublicHub, or the SageMaker public model catalog, transforming or validating training data, evaluating model quality, deploying or optimizing endpoints, configuring IAM/S3 for training, or managing SageMaker Managed MLflow. Use for endpoint health, failures, latency, logs, metrics, errors. Covers Serverless Model Customization, Nova and OSS deployment paths, and PySDK v3. NOT for Ground Truth labeling, Feature Store, or general-purpose AWS infrastructure.

日本語の概要は準備中です。原文の説明を表示しています。

Configure and use EAS Update for over-the-air JavaScript and asset updates with expo-updates and EAS CLI. Use when setting up OTA updates, running eas update:configure or eas update, publishing to preview/staging/production channels, explaining branches/channels/runtime versions, testing updates, or debugging why an installed build still shows old code. Load for TestFlight, preview, or production updates that do not appear, including questions about cold launches or reopening the app. Not for update health metrics; use eas-update-insights for adoption, crashes, and rollout monitoring.

日本語の概要は準備中です。原文の説明を表示しています。

Monitor Apple Notes automation health and performance metrics. Trigger: "apple notes monitoring".

日本語の概要は準備中です。原文の説明を表示しています。

Analyze DEX liquidity pools for TVL, volume, fees, impermanent loss, and LP profitability. Use when analyzing liquidity pools, calculating impermanent loss, or comparing DEX pools. Trigger with phrases like "analyze liquidity pool", "calculate impermanent loss", "LP returns", "pool TVL", "DEX pool metrics", or "compare pools".

日本語の概要は準備中です。原文の説明を表示しています。

Analyze code coverage metrics and identify untested code paths. Use when analyzing untested code or coverage gaps. Trigger with phrases like "analyze coverage", "check test coverage", or "find untested code".

日本語の概要は準備中です。原文の説明を表示しています。

Instrument an Algolia integration for actionable availability, latency, freshness, relevance, and event-health signals. Use when defining dashboards, alerts, traces, or service objectives. Trigger with "monitor Algolia", "Algolia metrics", or "search observability".

日本語の概要は準備中です。原文の説明を表示しています。

Measure and improve Abridge workflow latency and friction using privacy-safe health-system evidence. Use when clinicians report slow capture, note readiness, review, or EHR handoff. Trigger with "measure Abridge performance".

日本語の概要は準備中です。原文の説明を表示しています。

Transform weak resume bullets into achievement-focused statements with metrics and impact

日本語の概要は準備中です。原文の説明を表示しています。

Find opportunities to add metrics and estimate numbers when exact data unavailable

日本語の概要は準備中です。原文の説明を表示しています。